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Traffic Network Identification Using Trajectory Intersection Clustering

Gerdes, Ingrid and Temme, Annette (2020) Traffic Network Identification Using Trajectory Intersection Clustering. Aerospace, 7 (12). Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/aerospace7120175. ISSN 2226-4310.

[img] PDF - Postprint version (accepted manuscript)

Official URL: https://www.mdpi.com/2226-4310/7/12/175


The current airspace route system consists mainly of pre-defined routes with a low number of intersections to facilitate air traffic controllers to oversee the traffic. Our aim is a method to create an artificial and reliable route network based on planned or as-flown trajectories. The application possibilities of the resulting network are manifold, reaching from the assessment of new air traffic management (ATM) strategies or historical data to a basis for simulation systems. Trajectories are defined as sequences of common points at intersections with other trajectories. All common points of a traffic sample are clustered, and, after further optimization, the cluster centers are used as nodes in the new main-flow network. To build almost-realistic flight trajectories based on this network, additional parameters such as speed and altitude are added to the nodes and the possibility to take detours into account to avoid congested areas is introduced. As optimization criteria, the trajectory length and the structural complexity of the main-flow system are used. Based on these criteria, we develop a new cost function for the optimization process. In addition, we show how different traffic situations are covered by the network. To illustrate the capabilities of our approach, traffic is exemplarily divided into separate classes and class-dependent parameters are assigned. Applied to two real traffic scenarios, the approach was able to emulate the underlying route systems with a difference in median trajectory length of 0.2%, resp. 0.5% compared to the original routes.

Item URL in elib:https://elib.dlr.de/139515/
Document Type:Article
Title:Traffic Network Identification Using Trajectory Intersection Clustering
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Temme, AnnetteUNSPECIFIEDhttps://orcid.org/0000-0001-8245-3473UNSPECIFIED
Date:December 2020
Journal or Publication Title:Aerospace
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
EditorsEmailEditor's ORCID iDORCID Put Code
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Topical Collection "Air Transportation—Operations and Management"
Keywords:trajectory clustering; air traffic simulation; DBSCAN; airspace route network; common points
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Efficient Flight Guidance (old)
Location: Braunschweig
Institutes and Institutions:Institute of Flight Guidance > Controller Assistance
Institute of Flight Guidance > Pilot Assistance
Deposited By: Gerdes, Ingrid
Deposited On:11 Dec 2020 08:45
Last Modified:24 Oct 2023 15:14

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